학술논문

Social Alignment Contagion in Online Social Networks
Document Type
Periodical
Source
IEEE Transactions on Computational Social Systems IEEE Trans. Comput. Soc. Syst. Computational Social Systems, IEEE Transactions on. 11(1):399-417 Feb, 2024
Subject
Computing and Processing
Communication, Networking and Broadcast Technologies
General Topics for Engineers
Social networking (online)
Behavioral sciences
Voting
Sociology
Decision making
Blogs
Systematics
Causal inference
social contagion theory
social network analysis
Language
ISSN
2329-924X
2373-7476
Abstract
Researchers have already observed social contagion effects in both in-person and online interactions. However, such studies have primarily focused on users’ beliefs, mental states, and interests. In this article, we expand the state of the art by exploring the impact of social contagion on social alignment, i.e., whether the decision to socially align oneself with the general opinion of the users on the social network is contagious to one’s connections on the network or not. The novelty of our work in this article includes: 1) unlike earlier work, this article is among the first to explore the contagiousness of the concept of social alignment on social networks; 2) our work adopts an instrumental variable approach to determine reliable causal relations between observed social contagion effects on the social network; and 3) our work expands beyond the mere presence of contagion in social alignment and also explores the role of population heterogeneity on social alignment contagion. Based on the systematic collection and analysis of data from two large social network platforms, namely, Twitter and Foursquare, we find that a user’s decision to socially align or distance from social topics and sentiments influences the social alignment decisions of their connections on the social network. We further find that such social alignment decisions are significantly impacted by population heterogeneity.